Scanning-laser ophthalmoscopes with adaptive optics (AO/SLO) are medical devices which are becoming increasingly common and increasingly useful for retina imaging. Such devices are able to take microscopic images of a retina with a pixel pitch in the order of microns, and can make the images of individual rods and cones of the eye visible to a doctor.
An image is formed by a device which scans a laser in a raster arrangement over the surface of the retina and senses the amount of light returned. A representative device has a frame rate of around 60 Hz, with a resonant scanner forming scan-lines at a rate of 12 kHz and a pixel clock around 5 MHz, and one representative image size is 400×400 pixels.
By taking a video sequence of images of the retina, instead of still images, the transit of blood cells can be detected, allowing analysis of the velocity of blood flow.
However, AO/SLO can contain substantial image distortion. In a patient who is awake, the eye is in constant motion. One form of this motion is referred to as saccades. Saccades can be extremely fast, causing strong spatial distortions in AO/SLO images. A saccade can cause a rapid translation of the field of view of the retina from image to image, sometimes resulting in shifts between two neighbouring images of more than half the width of the images. When the eye is moving during the raster scanning process, many image distortions are caused, and are analogous to shutter distortion in many modern cameras that use a charge-coupled device (CCD) as an image sensor. Such distortion can cause large changes to the aspect ratio of a single image when motion is in the slow-scan direction of the raster sequence (e.g. between lines), and substantial shearing when motion is in the fast-scan direction of the raster sequence (along a line). If a saccade begins, or ends, or changes direction in the middle of a scan, such distortions may change across the image, or may appear in combination. While it may be possible to analyse the velocity of blood flow with non-aligned images, for many doctors, or for automated software, it is much easier to analyse substantially still images that are well-aligned to a common coordinate system, in order to make a diagnosis.
With many images distorted, it can be difficult to choose a common coordinate system onto which all images should be mapped. One way to achieve such a common coordinate system is to select a relatively undistorted reference image to which all others are mapped. Manual selection of an undistorted reference image can be a tedious and time-consuming process.
When examining methods for selecting a reference image, it is important to distinguish between on-line systems and off-line systems. In an on-line system, images are aligned in real time for immediate display, thus the reference image can only be selected from images that have already occurred, and without knowledge of the position or quality of those images yet to be captured. In an off-line system, where images are processed after all have been collected, the reference image can be selected from all of the gathered images. As more knowledge is available to the selection algorithm, an off-line method can produce a better, albeit less timely, result.
A good reference frame can sometimes be selected by supplementing local quality measures, such as variance and mean intensity, with a mean distance measurement. For example, an on-line system may regard an image as of high quality when the mean distance from that image to recent images is of a smaller value than the mean distance of other images to recent images. However, while the distance between recent images might be small enough, it does not guarantee that a distance between the selected image and other images in a collection of images is acceptable. Furthermore, the mean distance of an image to a collection of images can be problematic in the presence of fast motion such as saccades, where an image falling between widely separated groups of images can have a lower mean distance than an image within one of the groups.
Moreover, while it is theoretically possible for off-line systems to provide a better result in comparison with an on-line approach, to achieve this, the off-line systems might need to exhaustively consider every possible pair of images in the collection, which is not efficient. Therefore, a need exists to provide a system and method for ophthalmic reference image selection in presence of fast motion.